Exercise Patterns for Physical AI

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Provides a structured template for creating hands-on exercises in a Physical AI textbook, covering exercise types (thought experiment, simulation, hardware integration, capstone) and a progressive difficulty curve. Useful for designing educational activities with clear validation criteria and hardware notes.

Sby Skills Guide Bot
ContentBeginner
6/2/2026
Claude CodeCursorWindsurfCopilot
#exercise-template#robotics-education#ros2#hands-on-pattern

Recommended for

Automated summary

This template provides a standardized structure for creating hands-on exercises in a Physical AI textbook, with sections like objectives, instructions, verification, and challenges.

Strengths

  • Clear and reproducible exercise format, reducing writing effort.
  • Includes varied exercise types: thought experiments, simulations, hardware integration.
  • Offers a difficulty progression aligned with textbook chapters.
  • Ensures explicit validation criteria and realistic time estimates.

Limitations

  • Specific to the Physical AI textbook and technologies like ROS 2, Jetson, RealSense.
  • May need adjustments for other domains or tools.
  • Does not cover background content creation, only exercise structure.
When to use it

Use this template when you need to design a standardized hands-on exercise for a technical textbook on robotics or physical AI.

When not to use it

Avoid this template if you are writing theoretical content without a practical component or if you are working in a very different field from robotics.

Security analysis

Safe
Quality score92/100

The skill contains only a template for educational exercises with benign ROS 2 commands. No destructive, exfiltrating, or obfuscated actions are present.

No concerns found

How this analysis is made

Examples

Generate ROS 2 Exercise
Create an exercise for Chapter 4 of the Physical AI textbook using the exercise-patterns skill. The exercise should be intermediate difficulty, about 30 minutes, and involve creating a ROS 2 publisher node that publishes joint states for a virtual robot arm.
Hardware Integration Exercise
Use the exercise-patterns skill to outline a hardware integration exercise for Chapter 12. The student should deploy a ROS 2 node to a Jetson Orin Nano to read RealSense depth data and visualize it on a workstation. Include validation steps and a challenge to stream over Wi-Fi.
Thought Experiment on Embodiment
Using the exercise-patterns skill, generate a thought experiment exercise for Chapter 1. Ask students to list five tasks that require physical embodiment which an LLM alone cannot accomplish. Include a difficulty of beginner and a time estimate of 15 minutes.

name: exercise-patterns description: Structure for creating hands-on exercises in the Physical AI textbook.

Exercise Template (Strict Format)

## Exercise X.Y: [Title]

**Difficulty**: [Beginner | Intermediate | Advanced]
**Time**: [15 min | 30 min | 1 hour | 2 hours]
**Hardware**: [Workstation | Jetson + RealSense | Unitree Robot]

### Objectives
By completing this exercise, you will:
- [Action verb] [specific skill] (e.g., "Create a ROS 2 publisher node")
- [Action verb] [specific skill] (e.g., "Visualize sensor data in RViz2")
- [Action verb] [specific skill] (e.g., "Deploy code to Jetson Orin Nano")

### Prerequisites
- Chapter X completed
- ROS 2 Humble installed
- [Specific hardware setup, e.g., "RealSense D435i connected"]

### Instructions

#### Step 1: [Action]
```bash
# Command to run
ros2 pkg create my_package --build-type ament_python

Expected Output:

Successfully created package 'my_package'

Step 2: [Action]

[Detailed instructions with code snippets]

Step 3: [Verification]

Run this command to verify:

ros2 topic list

Expected: You should see /my_topic in the list.

Validation Checklist

  • [ ] Code compiles without errors (colcon build)
  • [ ] Node runs and publishes data (ros2 topic echo /my_topic)
  • [ ] RViz2 displays data correctly

Challenge (Optional)

[Extended task for advanced students, e.g., "Modify the node to publish at 100 Hz instead of 10 Hz"]

Troubleshooting

Problem: "Package not found" Solution: Source your workspace (source install/setup.bash)

Problem: "Topic not visible" Solution: Check if node is running (ros2 node list)


## Exercise Types

### 1. Thought Experiment (No Code)
**Format**: Conceptual questions to build intuition
**Example**: "List 5 tasks that require physical embodiment that an LLM alone cannot do"

### 2. Simulation Task (Gazebo/Isaac Sim)
**Format**: Code + Launch files + Gazebo world
**Example**: "Spawn a humanoid in Gazebo and make it walk forward 2 meters"

### 3. Hardware Integration (Jetson + Sensors)
**Format**: Deploy ROS 2 node to Jetson, read sensor data
**Example**: "Stream RealSense depth images to your workstation via Wi-Fi"

### 4. Capstone Project (Multi-Week)
**Format**: Complete system with milestones
**Example**: "Build an autonomous room-cleaning robot"

## Progressive Difficulty Curve

**Beginner** (Chapters 1-5):
- Copy-paste code examples
- Run pre-built packages
- Simple parameter changes

**Intermediate** (Chapters 6-15):
- Modify existing code
- Create new nodes
- Integrate multiple sensors

**Advanced** (Chapters 16-28):
- Design complete systems
- Optimize for hardware (Jetson)
- Implement novel algorithms
- Deploy to real robots

## Validation Standards
Every exercise must have:
1. **Clear Success Criteria** - "You should see X" or "The robot should do Y"
2. **Runnable Code** - Copy-paste should work without modification
3. **Hardware Note** - Explicitly state if Jetson/Robot required
4. **Time Estimate** - Realistic completion time for average student

From the file to a first result

The download contains exactly the content displayed on this page. This copy may differ from the latest version in the source repository.

View the source and supporting files

This download contains SKILL.md only. Any scripts, references, templates and dependencies are not included. Get the required files from the source, preserving their directory structure, before continuing.

1. Download the file

Download SKILL.md

From the root of a test project, save the file as .skill-downloads/exercise-patterns-for-physical-ai-mmh8qrfo/SKILL.md, or use the command below. This folder is for inspecting the skill before installation.

Command for macOS/Linux or WSL: requires a POSIX shell and curl. On Windows without WSL, use the download button and create the folder manually.

mkdir -p '.skill-downloads/exercise-patterns-for-physical-ai-mmh8qrfo' && curl --fail --show-error --location 'https://skills-guides.com/api/skills/exercise-patterns-for-physical-ai-mmh8qrfo/download' --output '.skill-downloads/exercise-patterns-for-physical-ai-mmh8qrfo/SKILL.md.part' && mv '.skill-downloads/exercise-patterns-for-physical-ai-mmh8qrfo/SKILL.md.part' '.skill-downloads/exercise-patterns-for-physical-ai-mmh8qrfo/SKILL.md'

2. Check prerequisites

Read SKILL.md before using it. If it references scripts or external services, inspect them and prepare the required access in your test environment.

No recognized prerequisites section in this file. This does not mean it is self-contained: libraries, tools and access requirements may be mentioned elsewhere in the content or source repository.

The platforms on this page are catalog indications. The paths below follow tool documentation; they do not prove this skill has been run in those tools. No minimum tool version is confirmed for this listing.

3. Load the skill

After inspection, copy the complete folder into your project using one of the commands below, then open a new tool session. The command stops if a folder with the same name already exists: compare the files before replacing it.

Claude Code
test -f '.skill-downloads/exercise-patterns-for-physical-ai-mmh8qrfo/SKILL.md' && test -s '.skill-downloads/exercise-patterns-for-physical-ai-mmh8qrfo/SKILL.md' && mkdir -p '.claude/skills' && test ! -e '.claude/skills/exercise-patterns' && cp -R '.skill-downloads/exercise-patterns-for-physical-ai-mmh8qrfo' '.claude/skills/exercise-patterns'

Cursor
test -f '.skill-downloads/exercise-patterns-for-physical-ai-mmh8qrfo/SKILL.md' && test -s '.skill-downloads/exercise-patterns-for-physical-ai-mmh8qrfo/SKILL.md' && mkdir -p '.cursor/skills' && test ! -e '.cursor/skills/exercise-patterns' && cp -R '.skill-downloads/exercise-patterns-for-physical-ai-mmh8qrfo' '.cursor/skills/exercise-patterns'

OpenSkills

OpenSkills must already be installed. The local install/read procedure is checked with OpenSkills 1.5.0, which requires Node.js ≥ 20.6.0. Catalog slugs are not resolved automatically.

Official OpenSkills installation
openskills install './.skill-downloads/exercise-patterns-for-physical-ai-mmh8qrfo'

openskills read 'exercise-patterns-for-physical-ai-mmh8qrfo'

Reading should display the installed file content and its base directory. It does not run the skill or install its dependencies.

For an agent that reads AGENTS.md, then sync the index. This command changes AGENTS.md: review the diff before using it.

openskills sync

Manual method or another tool: attach SKILL.md to a conversation, or open it in an agent that can read files. Include any required supporting resources. No universal folder is recognized by every tool.

4. Try a first task

Use a short, synthetic input: an API endpoint, a small document or an interface brief. In a new conversation, attach the file or give the agent its path, then adapt this request:

Read .skill-downloads/exercise-patterns-for-physical-ai-mmh8qrfo/SKILL.md and apply its instructions to this example: [describe a test input]. Identify any missing files, dependencies or access. Produce the result requested by the skill without inventing data or running unreviewed scripts.

Expected result: output matching the skill instructions, or a precise list of missing prerequisites. A read confirmation alone does not validate a first use. If an external resource is unavailable, that path remains untested.

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